In many online systems, users may submit product reviews, answer questions, or otherwise provide their opinion. For example, an online retail store may allow users to review products. These reviews provide information to consumers in order to judge the quality of a product before purchase. In another example, some online sites allow a community of experts (e.g., Subject Matter Experts, or “SMEs,” etc.) to answer questions, and each answer is ranked and rated by the community. In response, the community ranks the user's post in terms of quality, accuracy, or overall helpfulness. In this manner, user posts may establish credibility and be regarded as “high quality.” Posts that are not ranked as “helpful” by the community are often driven out of sight or ranked at the bottom of the page, while posts that are considered to be helpful are usually prominently displayed as a credible, or helpful, answer or review. In another context, a Question/Answer (QA) system is used to answer user questions posed in a natural language format. One aspect in a QA system is by using screened SMEs. In a QA system environment, the SMEs are people that evaluate information and identify whether it provides supporting evidence for the answer in the QA system. The SME's feedback is used to produce an answer key and, hopefully, better results from the QA system. This takes time, effort, and investment in the SMEs. A challenge faced by SMEs is that the SME often does not know beforehand what the community will regard as a thorough and helpful post or review. If the SME is unable to effectively communicate a response to a product or question, the SME's response will not be well received by the community regardless of the SME's experience and qualifications.